Shi Gu
18 papers · 2021–2026 · 8 venues · across top CS/AI venues
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Research topics
Deep Learning
(11)
Machine Learning
(10)
Artificial Intelligence
(9)
Architectures
(9)
Core AI
(9)
Optimization & Theory Β· Machine Learning
(4)
Techniques
(4)
Computer Vision
(3)
Analysis
(3)
Application Areas
(3)
Core Methods
(2)
Optimization & Theory Β· Deep Learning
(2)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Keywords
spiking neural network
(9)
spiking neuron
(3)
surrogate gradient
(3)
neuromorphic computing
(3)
energy efficiency
(2)
model compression
(2)
gradient descent
(2)
neuromorphic hardware
(2)
event-driven computing
(2)
concept bottleneck model
(2)
information bottleneck
(1)
medical image segmentation
(1)
model interpretability
(1)
knowledge distillation
(1)
adversarial robustness
(1)
post-training quantization
(1)
event camera
(1)
adversarial attack
(1)
model robustness
(1)
image classification
(1)
Papers
Dynamic-Static Decomposition for Novel View Synthesis of Dynamic Scenes with Spiking Neurons
CVPR 2026
eRetinexGS: Retinex Modeling for Low-Light Scene Enhancement via Event Streams and 3D Gaussian Splatting
CVPR 2026
On the Role of Temporal Granularity in the Robustness of Spiking Neural Networks
CVPR 2026
Robust Spiking Neural Networks by Temporal Mutual Information
CVPR 2026
Rounded or Streamlined Head? Bridging Concept Bottleneck Models and Attribute-Described Object Parts
CVPR 2026
SΒ³: Spiking Neurons as an Isolating Segmenter for Brain Signal Decoding
AAAI 2026
SPEAK: Spiking Neurons as an Entropy-Aware Tokenizer for Large Language Models
ACL 2026
Hybrid Concept Bottleneck Models
CVPR 2025
Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness
ICLR 2025
Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks
NeurIPS 2024
Train Once, Deploy Anywhere: Edge-Guided Single-source Domain Generalization for Medical Image Segmentation
MIDL 2024
Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks
ICML 2023
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
ICLR 2022
A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration
ICML 2021
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
ICLR 2021
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks
NeurIPS 2021
MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing
ICCV 2021
Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
ICLR 2021